How much actual math in PhD programs - (once you're there, not to get in)

[Weary]

Now if we start modelling the situation, registration for real analysis should improve one`s chances as exposure to a grad-like course should scare some students away from applying, working for those who still submit their forms.
Now who`s to collect the data?

[user_name]

Originally Posted by Weary

Now if we start modelling the situation, registration for real analysis should improve one`s chances as exposure to a grad-like course should scare some students away from applying, working for those who still submit their forms.

One can register and then drop. So the registration alone is probably not enough. But if one has taken other similar math courses and got good grades, it's reasonable to presume that one would not drop the course and would probably get a decent grade.

[econdude]

Isn't the point of taking these math courses to be "framiliar" with the material? I would think that the admissions committee would be ok with a student with good math grades in previous courses and being currently enrolled in RA or linear.

If this is not the case, one would have to wait an entire year before applying again. Is that the basic situation someone is in if they havn't taken the math courses and realize they want to apply for the next September? Dosn't seem right.

[gredow]

this is the situation i am in. do you think that in the space of 11 months i can take cal. 2-3, linear algebra & analysis? (while working the whole time)

[OneMoreEcon]

You should be "familiar" in the sense that you comprehend the content of the course. Many people have problems with analysis and the abstract nature of the topic. That's why grades matter, especially with regard to analysis. I said this on another thread, but analysis is the first course that really tells math professors whether a student has the potential to study math at a higher level (i.e. MA/PhD in math). Before that, everything is plug-&-chug.

gredow, the question is somewhat tough. The issue isn't whether or not you could do the material; it's whether or not the courses are offered. You could definitely do Calc 2-3 and linear algebra in two semesters (since 2 is an obvious pre-req for 3). That probably leaves analysis for the summer, and most schools probably won't teach it then (though you can find some, as this came up a few months ago on TM). The main problem you'll face with PhD admissions this year is that you'll only have grades for Calc 2 and maybe linear algebra, and many other applicants (at say top 30 or 40 schools) will have grades for more math courses. And the Stewart book you asked about on another thread is the one I used for Calc 1-3.

[tele82]

For first year core courses, they don't use much math actually. What u need is: Linear algebra+calculus+intro probablity+intro stats+a little analysis+a little ODE+comfortable working with math/logic things+economis intuition then you're ok. And the absolute difficulty level is lower than the typical real analysis course(I mean the content, not the test. real analysis tests are always easy. Prof cant fail the whole class ). Not sure about high level courses, but if you want to concentrate on finance. I think high level probability like brownian motion is necessary which means u have to be familar with measure and PDE.

Originally Posted by gredow

this is the situation i am in. do you think that in the space of 11 months i can take cal. 2-3, linear algebra & analysis? (while working the whole time)

if u'r not feeling tired after work now, I think you can do it. And u don't need to study calculus first in order to study analysis. Analysis course will build everything from axioms.

[dafrk3in]

I am currently taking the econ phd courses (Micro, Macro, Math for Econ). A solid understanding of basic real analysis is great, but a solid understanding of logic is absolutely essential. For example, you need to know how to work with quantifers: if you need to prove that for all x in R and all L>=1, f(Lx)<=Lf(x), how do you structure your proof? If you cannot answer this, then you have work to do before entering a phd program.

[Zavera]

At OSU you might as well quit if you don't have real analysis.

[ramlau]

Originally Posted by tele82

For first year core courses, they don't use much math actually. What u need is: Linear algebra+calculus+intro probablity+intro stats+a little analysis+a little ODE+comfortable working with math/logic things+economis intuition then you're ok.

Which school are we talking about?

Ram

[Mathman]

My 1.5 cents:

From what I understand, the analysis is helpful to formalize rigor in proof theory, etc. Epsilon/delta arguments, dealing with sequences/series, and understanding basic topological ideas like open/closed balls, etc come in handy in the heavy proof courses. For some people this may come naturally, but for us mere mortals it is difficult to pick these things up as econ phd courses tend to move quickly. Keep in mind that this is second hand info, and that I have yet to take a PhD level econ course (all my grad work is in math).

I have also heard that some top 50-30 schools will accept people without real analysis in the hope that they can pick up the ideas as they move along (placing the student in an uphill battle from the start).

With all of this said, I would suggest taking RA even if it comes too late for the admissions process. I really don't believe a person can be over-prepared in mathematics. The best voices on this subject are those already in programs. Zavera, Ramlau?, Snappy, etc

hope this is somewhat helpful, or at least entertaining.

Roger

Originally Posted by gredow

this is the situation i am in. do you think that in the space of 11 months i can take cal. 2-3, linear algebra & analysis? (while working the whole time)

With all do respect, 11 months is impossible. This may be possible in 3-4 semesters, however, depending on your universities prerequisites. In my program, linear requires cal III , and analysis requires cal III and a introductory proof course called foundations of mathematics or possibly discrete math.

Roger